Data report · 2026

North Carolina Water Damage Risk Index

Where in North Carolina is a house most likely to take on water? We combined Census housing age with ten years of daily weather for 100 of North Carolina's 100 counties to rank them.

Highest index

Burke

Score 72 of 100

Most pipe-freeze nights

Avery

27 nights ≤ 20°F a year

Oldest housing

Stanly

31% built before 1960

Most heavy-rain days

Transylvania

19.7 days ≥ 1 inch a year

< 4040–4747–5656–61≥ 61 index (0–100)

Key findings

The five highest-scoring counties are Burke, Surry, Caldwell, Haywood, McDowell. Each combines old housing with harsher-than-average winters or frequent downpours.
Stanly County has the oldest housing in the state, with 31% of homes built before 1960, against a county median of 18%.
Avery County averaged 27 nights a year at 20°F or colder, the most of any county in the data. The county median is 5.
Brunswick County has the newest housing, with 56% of homes built since 2000, which pulls its index down even where winters are cold.

Weather: NOAA nClimGrid-Daily county averages, 2015–2024. Housing: ACS 2020-2024.

All counties

Select a column header to sort.

Rank	County	Index	Freeze nights	Pre-1960 homes	Heavy-rain days	Muggy nights
1	Burke	72	10	23%	13.4	57
2	Surry	71	10	23%	13.3	52
3	Caldwell	70	10	22%	14.2	50
4	Haywood	70	23	23%	12.6	0
5	McDowell	70	11	19%	16.6	39
6	Polk	68	6	22%	16.6	70
7	Rutherford	68	7	24%	13.3	70
8	Mitchell	66	26	30%	10.6	0
9	Transylvania	66	12	17%	19.7	11
10	Wilkes	66	10	20%	14.2	51
11	Alleghany	65	21	17%	15	6
12	Martin	64	4	29%	11.8	99
13	Hyde	63	1	24%	14.7	122
14	Lenoir	63	4	23%	12.5	100
15	Pasquotank	63	4	24%	11.9	104
16	Rockingham	62	8	26%	10.9	78
17	Tyrrell	62	2	28%	13	115
18	Chowan	61	3	23%	12.8	107
19	Edgecombe	61	5	27%	11.3	90
20	Vance	61	8	21%	11.6	80
21	Ashe	60	25	16%	13.2	0
22	Henderson	60	11	14%	15.1	24
23	Washington	60	3	21%	13.6	106
24	Beaufort	59	2	24%	12.8	109
25	Hertford	59	5	23%	11.4	92
26	Northampton	59	7	21%	11.4	90
27	Stanly	59	4	31%	11.1	93
28	Avery	58	27	13%	13.3	0
29	Bertie	58	4	22%	11.9	98
30	Caswell	58	9	22%	10.9	74
31	Clay	58	14	12%	16	5
32	Buncombe	57	15	21%	10.9	10
33	Swain	57	22	12%	14.3	0
34	Yancey	57	26	16%	12.1	0
35	Gates	56	5	20%	11.7	91
36	Halifax	56	6	26%	10.4	88
37	Jackson	56	19	11%	16	1
38	Macon	56	15	10%	16.2	2
39	Perquimans	56	4	19%	12.5	103
40	Wilson	56	5	19%	12.1	94
41	Graham	55	19	11%	14.6	3
42	Jones	55	3	21%	13.2	101
43	Anson	54	3	28%	10.9	103
44	Greene	54	4	19%	12.5	100
45	Person	54	9	21%	10.8	71
46	Cherokee	53	15	10%	14.4	13
47	Watauga	53	24	11%	13.5	0
48	Yadkin	53	10	20%	10.5	66
49	Gaston	52	4	23%	11.1	89
50	Alamance	51	6	21%	10.8	80
51	Columbus	51	2	19%	12.9	115
52	New Hanover	51	2	14%	16.5	123
53	Rowan	51	6	24%	9.6	80
54	Stokes	51	9	13%	12.4	73
55	Forsyth	48	8	20%	9.9	78
56	Guilford	48	7	18%	10.9	82
57	Pamlico	48	1	14%	15.3	118
58	Warren	48	8	14%	11.1	83
59	Catawba	47	7	18%	11.1	76
60	Duplin	47	3	18%	12.5	101
61	Wayne	47	4	16%	11.6	101
62	Nash	46	6	18%	10.8	85
63	Alexander	45	9	18%	10.5	64
64	Bladen	45	3	17%	11.6	108
65	Carteret	45	1	11%	16.2	126
66	Cleveland	45	7	20%	10	76
67	Craven	45	2	14%	13.6	108
68	Granville	45	8	15%	10.9	78
69	Madison	45	15	19%	7.4	20
70	Montgomery	44	3	20%	11.1	95
71	Sampson	44	3	18%	11.6	101
72	Durham	43	7	14%	11.1	80
73	Onslow	43	3	8%	14.8	112
74	Pender	43	3	9%	14.8	113
75	Orange	42	7	11%	11.6	77
76	Richmond	42	3	22%	9.3	105
77	Davidson	41	6	19%	9.6	81
78	Randolph	41	5	18%	10.4	86
79	Franklin	40	7	11%	11.1	83
80	Pitt	40	4	10%	12.3	101
81	Brunswick	39	2	3%	15.5	122
82	Cabarrus	39	5	16%	10.4	87
83	Scotland	39	3	19%	10.4	107
84	Camden	38	4	11%	11.4	103
85	Davie	38	8	14%	9.1	78
86	Iredell	36	8	12%	10.1	75
87	Lincoln	36	6	12%	10.5	81
88	Robeson	36	3	15%	10.5	110
89	Johnston	35	4	10%	11.4	97
90	Dare	33	2	6%	12.3	126
91	Wake	33	5	5%	11.4	90
92	Currituck	32	3	6%	11.5	115
93	Chatham	31	5	12%	9.9	90
94	Harnett	30	4	11%	10	98
95	Lee	29	4	13%	9	96
96	Mecklenburg	27	4	9%	10.6	92
97	Moore	24	3	11%	9.9	98
98	Cumberland	22	3	10%	9.8	105
99	Hoke	22	3	7%	10.3	103
100	Union	22	4	7%	8.9	96

Methodology

For each county with weather data, we convert four factors to a percentile rank among those counties (0 = lowest, 100 = highest), then take a weighted average:

Pipe-freeze nights (nights ≤ 20°F / yr), weight 30%
Homes built before 1960 (% of homes), weight 30%
Heavy-rain days (days ≥ 1 in / yr), weight 25%
Muggy nights (nights ≥ 65°F / yr), weight 15%

Freezing weather and old plumbing get the most weight because burst and failing supply lines are among the most common causes of household water damage. Heavy rain drives basement flooding and sewer backups, and warm, muggy nights mark the humid air that lets mold follow. The index is relative: a low score means lower risk than other North Carolina counties, not no risk.

Limits: weather values are county-wide averages, so hollows, ridges and lakeshores can differ; ACS housing figures are survey estimates; the index doesn't account for floodplains, soil, or local sewer systems. Full details on our data sources page.

Cite this data

You're welcome to use these figures with attribution. Suggested citation:

Local Water & Mold, "North Carolina Water Damage Risk Index 2026," https://localwatermold.com/north-carolina/north-carolina-water-damage-risk/. Data: U.S. Census Bureau ACS 2020-2024; NOAA nClimGrid-Daily 2015–2024.